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Using big data to solve the XVA compute challenge

Derivatives pricing has changed dramatically over the past decade with an explosion in the number of valuation adjustments (XVAs) required. Traditional credit valuation adjustment systems are struggling to accurately calculate and manage these multiple XVAs and deliver a consistent view of all the trades in a portfolio. 

In this video, Stuart Nield and Abhay Pradhan of IHS Markit’s Financial Risk Analytics team discuss these challenges and highlight some of the modern technologies that can help overcome the compute and data issues.

00:00 Introduction
00:35 Key challenges of derivatives valuation (MVA, CVA, KVA)
04:13 Solving the compute and data challenge
06:55 Replacing legacy systems using open source technology
07:32 New technology cost savings and efficiency gains
09:54 Preparing for a tech-driven future

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